Researchers optimize genetic tests for diverse populations to tackle health disparities

Feb. 21, 2024
Improved genetic tests more accurately assess disease risk regardless of genetic ancestry.

To prevent an emerging genomic technology from contributing to health disparities, a scientific team funded by the National Institutes of Health has devised new ways to improve a genetic testing method called a polygenic risk score.

Since polygenic risk scores have not been effective for all populations, the researchers recalibrated these genetic tests using ancestrally diverse genomic data. As reported in Nature Medicine, the optimized tests provide a more accurate assessment of disease risk across diverse populations.

In the new study, the researchers improved existing polygenic risk scores using health records and ancestrally diverse genomic data from the All of Us Research Program, an NIH-funded initiative to collect health data from over a million people from diverse backgrounds.

The All of Us dataset represented about three times as many individuals of non-European ancestry compared to other major datasets previously used for calculating polygenic risk scores. It also included eight times as many individuals with ancestry spanning two or more global populations. Strong representation of these individuals is key as they are more likely than other groups to receive misleading results from polygenic risk scores.

The researchers selected polygenic risk scores for 10 common health conditions, including breast cancer, prostate cancer, chronic kidney disease, coronary heart disease, asthma and diabetes. Polygenic risk scores are particularly useful for assessing risk for conditions that result from a combination of several genetic factors, as is the case for the 10 conditions selected. Many of these health conditions are also associated with health disparities.

The researchers assembled ancestrally diverse cohorts from the All of Us data, including individuals with and without each disease. The genomic variants represented in these cohorts allowed the researchers to recalibrate the polygenic risk scores for individuals of non-European ancestry.

With the optimized scores, the researchers analyzed disease risk for an ancestrally diverse group of 2,500 individuals. About 1 in 5 participants were found to be at high risk for at least one of the 10 diseases.

Most importantly, these participants ranged widely in their ancestral backgrounds, showing that the recalibrated polygenic risk scores are not skewed towards people of European ancestry and are effective for all populations.

NIH release